Overview
Customer service is at the heart of customer satisfaction, retention, and brand reputation. As customer expectations rise and service channels multiply (email, chat, social media, calls), Artificial Intelligence (AI) is becoming a critical enabler for delivering faster, more consistent, and more personalised customer experiences.
Advances in Generative AI, Large Language Models (LLMs), and conversational AI allow customer service teams to respond more efficiently, handle higher volumes, standardise service quality, and support agents in real time—without replacing the human touch. AI can assist across the entire customer service lifecycle, from inquiry handling and complaint resolution to knowledge management, reporting, and service improvement.
This course provides a practical, customer-service-focused introduction to AI. Participants will learn AI fundamentals, understand how different AI tools support service workflows, and gain hands-on experience using leading GenAI tools to improve response quality, speed, and professionalism—while maintaining empathy, ethics, and organisational standards.
Skills Covered
By the end of this course, participants will be able to:
- Understand core AI concepts relevant to customer service operations
- Distinguish between AI, Machine Learning, LLMs, chatbots, and Generative AI
- Evaluate and select AI tools suitable for customer service workflows
- Use AI to draft, improve, and standardise customer responses
- Apply AI to complaint handling, FAQs, and knowledge base creation
- Improve service efficiency without losing empathy or professionalism
- Use AI responsibly within ethical, legal, and organisational boundaries
Prerequisites
There are no prerequisites required to attend this course.
Target Audience
This course is designed for professionals involved in customer-facing and service support roles, including:
- Customer service and support officers
- Call centre and contact centre staff
- Customer experience (CX) teams
- Helpdesk and service desk personnel
- Frontline supervisors and team leaders
- Operations and service quality managers
- Sales support and after-sales service teams
No prior AI or technical background is required.
Module 1: Understanding AI for Customer Service
- What Artificial Intelligence is and is not
- Relationship between:
- Artificial Intelligence
- Machine Learning
- Conversational AI
- Large Language Models (LLMs)
- Generative AI
- How AI supports customer service:
- faster response handling
- consistency across agents
- knowledge retrieval
- customer sentiment understanding
- Strengths and limitations of AI in customer service
Module 2: AI Tools Landscape for Customer Service Teams
- Overview of AI tools for customer service:
- ChatGPT, Gemini, Copilot, Claude
- Perplexity, Grok, Manus, DeepSeek, Qwen, NotebookLM
- Differences in tools for:
- customer communication
- response accuracy and tone
- summarisation and knowledge search
- Selecting the right AI tool for:
- email and chat responses
- complaint handling
- internal support and escalation notes
- Prompt engineering fundamentals for service scenarios
Hands-On Activities
- Writing prompts for customer inquiries and complaints
- Comparing empathetic vs non-empathetic AI responses
- Refining tone, clarity, and professionalism
Module 3: AI for Customer Communication and Response Writing
- Using AI to:
- draft customer emails and chat replies
- adjust tone (polite, empathetic, firm, apologetic)
- personalise responses at scale
- Handling difficult customers with AI support
- Multilingual and simplified communication using AI
Hands-On Activities
- Drafting responses for common customer scenarios
- Improving response quality using AI feedback
Module 4: Responsible AI, Ethics, and Trust in Customer Service
- Risks of AI in customer service:
- inaccurate or misleading responses
- loss of human empathy
- inconsistent service tone
- Data privacy and customer confidentiality
- Human-in-the-loop customer service models
- When AI should support vs when humans must lead
- Best practices for responsible AI use in customer interactions
Module 5: AI for Complaint Handling and Escalation
- AI-assisted complaint analysis and categorisation
- Drafting professional complaint responses
- Supporting escalation and resolution workflows
- Maintaining brand voice under pressure
Hands-On Activities
- Handling real-world complaint scenarios using AI
- Improving resolution clarity and tone
Module 6: AI for FAQs, Knowledge Base, and Self-Service
- Using AI to:
- create and maintain FAQs
- summarise policies and procedures
- support internal knowledge sharing
- NotebookLM for document-based service knowledge
- Reducing repetitive inquiries through AI
Hands-On Activities
- Generating FAQs from existing documents
Improving knowledge base clarity
Module 7: AI-Enabled Customer Service Workflow
- Designing AI-supported service workflows:
-
- inquiry → response → resolution → follow-up
- Integrating AI into daily service operations
- Improving response time, consistency, and quality
- Measuring service performance with AI support
Exercise
- Designing an AI-assisted customer service workflow
Module 8: AI Strategy for Customer Service Teams and Leaders
- Identifying high-impact AI opportunities in customer service
- Positioning AI as a service assistant, not a replacement
- Establishing AI usage guidelines and service standards
- Preparing customer service teams for AI-enabled roles
- Continuous improvement of customer experience using AI
Workshop
- Drafting a high-level AI adoption plan for a customer service team
Exam & Certification
This course is not associated with any Certification.
Training & Certification Guide
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